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marketplace

The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
actionNosearch
mcp_idNo
messageNo
tool_idNo
argumentsNo{}
immediateNo
tier_slugNo
prompt_bodyNo
prompt_slugNo
prompt_toolNo
prompt_varsNo{}
conversationNo[]
prompt_titleNo
request_nameNo
cancel_reasonNo
cancel_commentNo
prompt_targetsNo
report_contextNo
prompt_categoryNo
request_detailsNo
prompt_descriptionNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses important side effects and hidden behaviors: invoke performs a one-off install behind the scenes, auth-gated or unpaid tools return user-action links, and write operations require workspace owner/admin. These details go well beyond the generic annotations (readOnlyHint=false, destructiveHint=false) and align with them, adding genuine behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense and lengthy, but the tool itself is a broad multi-action dispatcher with 23 parameters and 15 sub-actions, so nearly every sentence adds necessary guidance. The flow-oriented structure (search → describe → invoke, then install, then prompt library) helps navigation, though bullet points or section breaks would improve scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core discovery-to-invocation loop, auth and wallet failure handling, permission requirements, one-off vs permanent install semantics, and the entire prompt-library subdomain. It does not explain return shapes, error/retry behavior, or some secondary parameters, and there is no output schema to compensate, but given the tool's complexity this is still a reasonably complete overview.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description compensates by explaining the key dispatcher parameters: action values, mcp_id usage in search/describe, tool_id selection for invoke, arguments for the invoke call, and prompt_slug/prompt_vars for prompt-library actions. However, several parameters like limit, query, immediate, tier_slug, conversation, cancel_reason, and report_context remain undocumented, so the compensation is strong but not complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies marketplace as the official in-platform catalog and execution path, with specific verbs for each sub-action: search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions. It also differentiates itself from sibling tools by positioning report_bug as one of its own sub-actions and framing the tool as the central MCP discovery and running mechanism.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance, especially 'Use install only to make an MCP PERMANENT' and 'prefer invoke for a single/occasional use.' It also explains conditional flows for auth and payment failures ('returns a connect link', 'returns a checkout/top-up link ... then you retry') and states that writes require workspace owner/admin, providing clear decision rules for the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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